Toward Long-Lasting Large-Scale Soft Robots: The Durability Challenge in Architectured Materials

Francesco Stella, Guanran Pei, Omar Meebed, Qinghua Guan, Zhenshan Bing, Cosimo Della Santina, Josie Hughes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Soft robots promise groundbreaking advancements across various industries. However, soft robots are susceptible to wear, fatigue, and material degradation. Their durability and long-term reliability are often overlooked, despite being critical for the successful deployment of these systems in real-world applications. This article contributes to solving this challenge by identifying metrics that reflect material wear, mechanical hysteresis, and drift occurring during long-term operations in soft architectured materials. While this same pipeline can be generalized to different soft robots, we test these metrics on the trimmed helicoid architectured materials, and we validate the improvement in performance on the Helix soft manipulator. Thanks to the proposed metrics, we demonstrate a 75% reduction in repeatability errors over long-duration experiments.

Original languageEnglish
Title of host publication2024 IEEE 7th International Conference on Soft Robotics, RoboSoft 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages190-196
Number of pages7
ISBN (Electronic)9798350381818
DOIs
StatePublished - 2024
Externally publishedYes
Event7th IEEE International Conference on Soft Robotics, RoboSoft 2024 - San Diego, United States
Duration: 14 Apr 202417 Apr 2024

Publication series

Name2024 IEEE 7th International Conference on Soft Robotics, RoboSoft 2024

Conference

Conference7th IEEE International Conference on Soft Robotics, RoboSoft 2024
Country/TerritoryUnited States
CitySan Diego
Period14/04/2417/04/24

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